With the development of radio and space technologies, several satellites based navigation systems (i.e. satellite positioning system or “SPS”) have already been built and more will be in use in the near future. SPS receivers, such as, for example, receivers using the Global Positioning System (“GPS”, also known as NAVSTAR, have become commonplace. Other examples of SPS systems include, but are not limited to, the United State (“U.S.”) Navy Navigation Satellite System (“NNSS”) (also known as TRANSIT), LORAN, Shoran, Decca, TACAN, NAVSTAR, the Russian counterpart to NAVSTAR known as the Global Navigation Satellite System (“GLONASS”) and any future Western European SPS such as the proposed “Galileo” program. As an example, the U.S. NAVSTAR GPS system is described in GPS Theory and Practice, Fifth ed., revised edition by Hofmann-Wellenhof, Lichtenegger and Collins, Springer-Verlag Wien New York, 2001, which is fully incorporated herein by reference.
The U.S. GPS system was built and is operated by the United States Department of Defense. The system uses twenty-four or more satellites orbiting the earth at an altitude of about 11,000 miles with a period of about twelve hours. These satellites are placed in six different orbits such that at any time a minimum of six satellites are visible at any location on the surface of the earth except in the polar region. Each satellite transmits a time and position signal referenced to an atomic clock. A typical GPS receiver locks onto this signal and extracts the data contained in it. Using signals from a sufficient number of satellites, a GPS receiver can calculate its position, velocity, altitude, and time (i.e. navigation solution).
GPS and other satellite based navigational systems have some limitations such as dependence on the availability of a sufficient number of satellite signals, and/or dependence on strength of the available signals. Satellite signals are sometimes not available in deep canyon-like geographical environments, e.g., in areas with large number of tall buildings blocking the direct satellite signals, in dense forest areas, etc. In addition to this, the satellite signals can be completely blocked or greatly attenuated inside buildings, or at underground locations, such us subway stations in a metropolitan area, basement of a house/commercial building etc. Additionally, weak satellite signal may be corrupted by other stronger signals naturally or intentionally.
To reduce these errors, inertial measurement units (IMUs) equipped with sensors can be integrated with a navigation device to provide data that is used to improve the position predictability and reliability of the device in degraded signal environments. For example, in an indoor environment where satellite signals are not available or in a dense urban environment where multipath errors are common, sensor data can aid in the calculation of a navigation solution. Typical IMUs include gyroscopes that measure changes in direction, accelerometers that estimate acceleration, magnetic sensors that can detect changes in the orientation of a device, and a host of other similar devices. More particularly, after the position of a navigation device is initially determined, the IMUs allow the position of the navigation device to be determined as the navigation device moves, even if the satellite signals are blocked.
The determination of a position by propagating a previous known position based on movement data (e.g., data provided by an IMU) can be used is inertial navigation, such as a dead-reckoning (DR) method. DR methods do not typically take into account contextual information regarding how the navigation device is moving. Co-pending co-owned U.S. application Ser. No. 12/510,965, published as U.S. Publication No. 2011/0029277, titled, “Methods and Applications for Motion Mode Detection for Personal Navigation Systems,” advanced the state of the art by disclosing methods and apparatuses for detecting and using motion modes in a personal navigation device.
However, there is room for improvement in the use of motion data of a navigation device to enhance user experience by more accurately pinpointing a navigation device's location, and associating contextual/situational information with the user based on the device's detected location. For example, current methods are not optimized for precisely predicting the position of the navigation device on a person's body. Moreover, position detection algorithms are not optimized to exploit the inherent hierarchy in collected locational data obtained from the sensors.